An Overview of Perception Methods for Horticultural Robots: From Pollination to Harvest
It addresses automation needs for horticultural enterprises by summarizing existing work, but is incremental as it provides an overview rather than novel contributions.
This paper reviews sensing and perception methods for horticultural robots across pollination, yield estimation, and harvesting, highlighting challenges like unstructured environments and variable lighting, and surveys current research trends without presenting new experimental results.
Horticultural enterprises are becoming more sophisticated as the range of the crops they target expands. Requirements for enhanced efficiency and productivity have driven the demand for automating on-field operations. However, various problems remain yet to be solved for their reliable, safe deployment in real-world scenarios. This paper examines major research trends and current challenges in horticultural robotics. Specifically, our work focuses on sensing and perception in the three main horticultural procedures: pollination, yield estimation, and harvesting. For each task, we expose major issues arising from the unstructured, cluttered, and rugged nature of field environments, including variable lighting conditions and difficulties in fruit-specific detection, and highlight promising contemporary studies.